Protection against Alzheimer's disease (AD) dementia has two main components: protection against Alzheimer's disease pathology (ADP ? amyloid and tau) and protection against cognitive impairment despite ADP (cognitive reserve). Here, we propose an ?exceptional aging? hypothesis, where some subjects (>85 years of age) have no significant ADP and are cognitively normal due to protective factors against both ADP and cognitive decline across the lifespan. This is based on the idea that a combination of environmental, lifestyle, and genetic factors trigger the onset of AD dementia in the majority of individuals as they age but ?exceptional agers? are protected. To translate this knowledge to design successful personalized prevention and treatment trials, it is important to identify the parsimonious set(s) of protective factors and how certain individuals are able to outperform the average population trajectories, i.e., ?exceptionally age?. Our central hypothesis is that each individual's trajectory of amyloid, tau, and cognition will deviate from the average population trajectories, depending on the individual's genomic variation, lifestyle enrichment, and vascular health. The aim of this proposal is to apply the unified theoretical framework proposed here to identify important protective factors against ADP and cognitive decline in a population-based sample and move towards personalized medicine by discovering paths to ?exceptional aging? using two independent mathematical models (association rule mining and structural equation models). We will utilize the existing infrastructure of the population-based, longitudinal Mayo Clinic Study of Aging (MCSA) (individuals aged 60-90 years) which collects imaging surrogates of amyloid (PiB PET) and tau (tau PET), neuropsychological exams, lifestyle enrichment (midlife cognitive and physical activity), and APOE gene status. We will also utilize the Rochester Epidemiology Project (REP) which maintains a comprehensive medical records-linkage system (since 1965), to abstract additional information from the electronic medical records: longitudinal lab tests (lipid panel), blood pressure, medications, BMI, and diagnosis of cardiac and metabolic conditions (CMCs) up to 20 years before the amyloid and tau scans. Lastly, we will add a comprehensive screen of genetic variation related to ADP, related neurodegenerative disorders, and aging with the latest SNP-based array (NeuroX2).